Search Results for "deploy"

Expo is an open source framework and platform for creating universal React applications that run on Android, iOS, and the web. It includes a set of tools, services, universal runtime and libraries that let you develop, deploy and iterate on Android, iOS, and the web with the same JavaScript/TypeScript codebase. Expo is where client software is developed, and contains the client apps, modules, templates and more; while the Expo development tools are contained in the Expo CLI repository. Try Expo in the browser here: https://snack.expo.io/

...It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including Classical CNN (VGG AlexNet GoogleNet Inception), Face Detection (MTCNN RetinaFace), Segmentation (FCN PSPNet UNet YOLACT), and more. ncnn is currently being used in a number of Tencent applications, namely: QQ, Qzone, WeChat, and Pitu.

AngularFire smooths over the rough edges an Angular developer might encounter when implementing the framework-agnostic Firebase JS SDK & aims to provide a more natural developer experience by conforming to Angular conventions. Provide and Inject Firebase services in your components. Stable zones allow proper functionality of service workers, forms, SSR, and pre-rendering. Utilize RxJS rather than callbacks for realtime streams. Integrate with NgRx using AngularFire's action based APIs....

...The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.